AI & Machine Learning

Characterizing Human Semantic Navigation in Concept Production as Trajectories in Embedding Space

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Researchers have developed a framework to analyze how humans navigate semantic spaces when producing concepts, using geometric metrics derived from transformer text embeddings. This approach offers a computationally efficient method for studying cognitive processes across different languages and clinical conditions, potentially advancing applications in clinical research and cross-linguistic analysis.

Read the full article at arXiv cs.CL (NLP)

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